Abstract: An optical display apparatus is disclosed. A coupling apparatus couples light output by an image generation apparatus into an optical expansion waveguide. The optical expansion waveguide at least comprises a first reflective surface array and a second reflective surface array. Each reflective surface array is used for expanding, in an one-dimensional direction, light propagating through the optical expansion waveguide, so that the light entering into the optical expansion waveguide is expanded in a two-dimensional direction and is emitted outside of the optical expansion waveguide to form an image, wherein at least one of a first reflective surface of the first reflective surface array and a second reflective surface of the second reflective surface array is at least partially a curved surface, allowing the angle of emergence of the light to be changed by means of the first reflective surface or/and the second reflective surface.

Abstract: A system and method for performing automated learning of an Internet-of-Things (IoT) application are disclosed. The automated learning is based on generation of application-agnostic events, allowing the automated learning to be performed without prior knowledge of the IoT application.

Abstract: An optical expansion waveguide is disclosed that may comprise a first waveguide substrate (1) and a second waveguide substrate (2). The first waveguide substrate (1) allows the light entering the first waveguide substrate to expand in a first dimension direction, and the first waveguide substrate (1) comprises a plurality of first reflecting surfaces (101) arranged in sequence. The second waveguide substrate (2) allows the light entering the second waveguide substrate to expand in a second dimension direction, and the second waveguide substrate (2) comprises a plurality of second reflecting surfaces (201) arranged in sequence. At least one of the first reflecting surface (101) and the second reflecting surface (201) is at least partially curved so as to change an emission angle of light, such that the image distance of the image formed by the light emitted by the second waveguide substrate (2) meets the preset requirement.

Abstract: Techniques for detecting anomalous behavior of an Internet-of-Things (IoT) device in an IoT network. IoT events of an IoT device are captured and analyzed to identify periodic activities of the IoT device. The periodic activities of the IoT device are tracked over time, and variations in the periodic activities are analyzed to assess potential threats to the IoT network.

Abstract: Correlating Internet of Things (IoT) security events is disclosed. A set of security events is received. A graph is generated, where nodes of the graph correspond to at least some of the received security events in the set. The edges in the graph correspond to identifiable patterns of correlation. A determination of whether or not the generated graph matches a prebuilt scenario is determined and a remedial action is taken in response to the determination.

Abstract: A computer-implemented method includes determining a quantity of reserved resources that need to be reserved in one node. Nodes in which quantities of current remaining resources are less than a quantity of reserved resources are determined. For each determined node, calculating a total quantity of resources occupied by allocated service requests in the node and determining whether the node is capable of satisfying the quantity of reserved resources. If yes, marking the node as a migratable node. One migrating node is selected from migratable nodes and corresponding M allocated service requests are migrated to at least one other node. Resources occupied by the M allocated service requests are released, where M satisfies a condition that after the resources occupied by the M allocated service requests are released, a quantity of remaining resources in the migrating node is not less than the quantity of reserved resources.

Abstract: An anomalous behavior detector has been designed to detect novel behavioral changes of devices based on network traffic data that likely correlate to anomalous behaviors. The anomalous behavior detector uses the local outlier factor (LOF) algorithm with novelty detection. After initial semi-supervised training with a single class training dataset representing stable device behaviors, the obtained model continues learning frontiers that delimit subspaces of inlier observations with live network traffic data. Instead of traffic variables being used as features, the features that form feature vectors are similarities of network traffic variable values across time intervals. A feature vector for the anomalous behavior detector represents stability or similarity of network traffic variables that have been chosen as device identifiers and behavioral indicators.

Abstract: The present application relates to a service decision method and a service decision device. The method includes: receiving a task request sent by a terminal, the task request including a terminal identifier, terminal location information and task information of the terminal; determining that the terminal is currently in an overlapping coverage area, generating a decision-making instruction according to the task request and a target decision network, and sending the decision-making instruction to the terminal according to the terminal identifier, the decision-making instruction being used to indicate whether a target unmanned aerial vehicle server provides to the terminal a service corresponding to the task request, and the target decision-making instruction being used by the terminal to select one server from among the target unmanned aerial vehicle server and the other unmanned aerial vehicle servers to provide the service. Using the present method can improve resource utilization.

Abstract: Internet of Things (IoT) device application workload capture is disclosed. A target IoT device is selected. A flow associated with the target IoT device is determined and tagged. Packets from the tagged flow are admitted into a ring buffer. An indication is received that an extraction should be performed on a portion of the packets included in the ring buffer.

Abstract: Correlating Internet of Things (IoT) security events is disclosed. A set of security events is received. A graph is generated, where nodes of the graph correspond to at least some of the received security events in the set. The edges in the graph correspond to identifiable patterns of correlation. A determination of whether or not the generated graph matches a prebuilt scenario is determined and a remedial action is taken in response to the determination.

Abstract: A method and system for determining coastal erosion disaster early warning lines and calculating spatial scope thereof. The method includes determining a coastal erosion rate according to coastal erosion change monitoring data and landform data; and calculating at least one coastal erosion early warning line in coming N years in conventional conditions according to an established coastal erosion rate calculation method; determining the at least one coastal erosion early warning line in N years in extreme conditions by increasing influencing factors of accelerated sea level rise and extreme storm waves and utilizing a determination and calculation method of coastal erosion disaster early warning lines; and obtaining a coastal erosion retreat position and scope and sending early warning based on the coastal erosion rate in conventional conditions and the at least one coastal erosion early warning line in extreme conditions.

Abstract: The present disclosure provides a phosphorus-containing compound represented by Formula (1), a resin composition comprising the phosphorus-containing compound, and an article made from the resin composition. The phosphorus-containing compound can achieve halogen-free flame retardancy while satisfying the requirements of excellent dielectricity, high copper foil peeling strength, high glass transition temperature, low percent thermal expansion and excellent heat resistance after moisture absorption. The resin composition comprises the following components or a prepolymer thereof: (A) 100 parts by weight of an unsaturated C?C double bond-containing polyphenylene ether resin; and (B) 15 parts by weight to 90 parts by weight of the phosphorus-containing compound represented by Formula (1); wherein the prepolymer is obtained from a mixture through prepolymerization, and the mixture comprises at least the component (A) and the component (B).

Abstract: A lightning protective and heating porcelain tile includes a porcelain tile layer, a shell, a metal plate protective layer, and an electric heating film heating layer. The metal plate protective layer is attached to the inner wall of the porcelain tile layer, and the electric heating film heating layer is attached to the metal plate protective layer. The electric heating film heating layer includes an electric heating film, a first lightning protective module and a second lightning protective module. The hot wire and neutral wire connected to the electric heating film are electrically connected to the first lightning protective module and the second lightning protective module, respectively. The first lightning protective module and the second lightning protective module are electrically connected to the metal plate protective layer individually. The first lightning protective module and the second lightning protective module are made of varistors.

Abstract: A method and system for determining coastal erosion disaster early warning lines and calculating spatial scope thereof.

Abstract: A method for reckoning the environmental background water temperature and calculating the temperature rise in a temperature rise area of a newly-built coastal power plant is provided. The reckoning method includes: S01, before an operation of the newly-built coastal power plant, building a water temperature reference station; S02, continuously observing and recording water temperature data of the water temperature reference station and other water temperature observation stations; S03, analyzing the water temperature data obtained in S02; and S04, reckoning a sea surface natural water temperature of the other water temperature observation stations.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on computer storage media, for automated foodservice are described. An example method includes receiving one or more images from one or more cameras capturing a food container comprising a plurality of compartments; determining, using a first machine learning model based on the one or more images, a user action comprising a user taking food from a first compartment of the plurality of compartments; receiving a plurality of pieces of weight sensor data from a plurality of weight sensors coupled to a frame hosting the food container; determining, using a second machine learning model based on the plurality of pieces of weight sensor data, a second compartment of the plurality of compartments; in response to the first compartment being the same as the second compartment, displaying the weight and the food information of the food taken by the user.

Abstract: A seed development device for Psammochloa villosa using condensate water in desert areas includes: a cultivation box, a top surface of the cultivation box is connected to a cooler and condensate water collecting units through a support frame. Each condensate water collecting unit includes an outer frame, sleeve pipes, a middle frame, a cold air cavity, water collecting rods, a water collecting tank and a delivery pipe. The delivery pipe is connected to the cultivation box. When an outdoor temperature cannot complete condensation of water vapor, the cooler completes cooling of the cold air cavity and water collecting rods until condensate water collection is completed, water drops fall into the water collecting tank to complete water collection, which is used for water supplement of seed development of Psammochloa villosa, thus reducing the process of artificial water supplement and improving the development efficiency of seeds of Psammochloa villosa in desert areas.

Abstract: Techniques for grouping and labeling Internet of Things (IoT) devices are disclosed. A first set of raw events associated with a first IoT device is identified, including a transmission made by the first IoT device. A communication manner of the first IoT device is determined, based at least in part on a communication manner of the first IoT device. The first set of raw events over the first time period is examined to generate one or more formatted events of the first IoT device. The formatted events are used to extract a set of features. Similar processing is performed with respect to a second IoT device. A context-based IoT device grouping model is generated based on at least one of: (1) the features extracted for the first IoT device or (2) the features extracted for the second IoT device. The model is applied to determine that a third IoT device belongs to a particular group. A deviation by the third IoT device from group behavior is detected and an alert is generated in response.

Abstract: A seed development device for Psammochloa villosa using condensate water in desert areas includes: a cultivation box, a top surface of the cultivation box is connected to a cooler and condensate water collecting units through a support frame. Each condensate water collecting unit includes an outer frame, sleeve pipes, a middle frame, a cold air cavity, water collecting rods, a water collecting tank and a delivery pipe. The delivery pipe is connected to the cultivation box. When an outdoor temperature cannot complete condensation of water vapor, the cooler completes cooling of the cold air cavity and water collecting rods until condensate water collection is completed, water drops fall into the water collecting tank to complete water collection, which is used for water supplement of seed development of Psammochloa villosa, thus reducing the process of artificial water supplement and improving the development efficiency of seeds of Psammochloa villosa in desert areas.

Abstract: Embodiments of this specification provide batch scheduling-based application scheduling methods, apparatuses, and systems. In the batch scheduling-based application scheduling method, an application scheduling request is received from a client, where the application scheduling request includes description information used to indicate a chain invoking relationship between applications to be scheduled; the applications to be scheduled are grouped into at least one scheduling object group based on the chain invoking relationship, where applications to be scheduled that are located in the same scheduling object group have the same chain invoking relationship; and the applications to be scheduled are scheduled to a target node by using the scheduling object group as a unit.